Pathway Summary

Consort map

Demographic information

Characteristic

N

Overall, N = 701

control, N = 351

treatment, N = 351

p-value2

age

70

50.92 ± 12.67 (25 - 74)

50.48 ± 13.41 (25 - 74)

51.36 ± 12.06 (31 - 72)

0.775

gender

70

0.794

f

49 (70%)

24 (69%)

25 (71%)

m

21 (30%)

11 (31%)

10 (29%)

occupation

70

0.936

day_training

1 (1.4%)

1 (2.9%)

0 (0%)

full_time

6 (8.6%)

4 (11%)

2 (5.7%)

homemaker

6 (8.6%)

3 (8.6%)

3 (8.6%)

other

2 (2.9%)

0 (0%)

2 (5.7%)

part_time

13 (19%)

6 (17%)

7 (20%)

retired

15 (21%)

7 (20%)

8 (23%)

self_employ

2 (2.9%)

1 (2.9%)

1 (2.9%)

student

1 (1.4%)

0 (0%)

1 (2.9%)

t_and_e

2 (2.9%)

1 (2.9%)

1 (2.9%)

unemploy

22 (31%)

12 (34%)

10 (29%)

marital

70

0.924

cohabitation

1 (1.4%)

0 (0%)

1 (2.9%)

divore

8 (11%)

5 (14%)

3 (8.6%)

married

15 (21%)

7 (20%)

8 (23%)

none

40 (57%)

20 (57%)

20 (57%)

seperation

3 (4.3%)

2 (5.7%)

1 (2.9%)

widow

3 (4.3%)

1 (2.9%)

2 (5.7%)

edu

70

0.992

bachelor

20 (29%)

9 (26%)

11 (31%)

diploma

12 (17%)

7 (20%)

5 (14%)

hd_ad

3 (4.3%)

2 (5.7%)

1 (2.9%)

postgraduate

6 (8.6%)

3 (8.6%)

3 (8.6%)

primary

5 (7.1%)

2 (5.7%)

3 (8.6%)

secondary_1_3

7 (10%)

3 (8.6%)

4 (11%)

secondary_4_5

15 (21%)

8 (23%)

7 (20%)

secondary_6_7

2 (2.9%)

1 (2.9%)

1 (2.9%)

fam_income

70

0.918

10001_12000

4 (5.7%)

1 (2.9%)

3 (8.6%)

12001_14000

4 (5.7%)

2 (5.7%)

2 (5.7%)

14001_16000

5 (7.1%)

2 (5.7%)

3 (8.6%)

16001_18000

2 (2.9%)

1 (2.9%)

1 (2.9%)

18001_20000

4 (5.7%)

3 (8.6%)

1 (2.9%)

20001_above

10 (14%)

6 (17%)

4 (11%)

2001_4000

9 (13%)

6 (17%)

3 (8.6%)

4001_6000

10 (14%)

4 (11%)

6 (17%)

6001_8000

7 (10%)

4 (11%)

3 (8.6%)

8001_10000

6 (8.6%)

2 (5.7%)

4 (11%)

below_2000

9 (13%)

4 (11%)

5 (14%)

medication

70

60 (86%)

31 (89%)

29 (83%)

0.495

onset_duration

70

15.38 ± 11.60 (0 - 56)

16.98 ± 12.86 (1 - 56)

13.78 ± 10.13 (0 - 35)

0.251

onset_age

70

35.53 ± 13.88 (14 - 64)

33.50 ± 12.73 (14 - 58)

37.57 ± 14.86 (15 - 64)

0.222

1Mean ± SD (Range); n (%)

2Two Sample t-test; Pearson's Chi-squared test; Fisher's exact test

Measurement

Table

Characteristic

N

Overall, N = 701

control, N = 351

treatment, N = 351

p-value2

recovery_stage_a

70

3.14 ± 1.24 (1 - 5)

3.14 ± 1.29 (1 - 5)

3.14 ± 1.22 (1 - 5)

>0.999

recovery_stage_b

70

17.99 ± 2.63 (9 - 23)

17.86 ± 2.70 (9 - 23)

18.11 ± 2.59 (13 - 23)

0.686

ras_confidence

70

30.44 ± 4.78 (19 - 43)

29.71 ± 4.23 (19 - 40)

31.17 ± 5.24 (20 - 43)

0.205

ras_willingness

70

12.07 ± 1.95 (7 - 15)

11.94 ± 1.89 (9 - 15)

12.20 ± 2.03 (7 - 15)

0.585

ras_goal

70

17.59 ± 2.98 (12 - 24)

17.51 ± 3.00 (12 - 24)

17.66 ± 3.00 (12 - 24)

0.843

ras_reliance

70

13.20 ± 2.84 (8 - 20)

12.89 ± 2.60 (8 - 18)

13.51 ± 3.06 (8 - 20)

0.358

ras_domination

70

10.01 ± 2.16 (3 - 15)

10.43 ± 1.96 (6 - 15)

9.60 ± 2.30 (3 - 14)

0.110

symptom

70

30.06 ± 9.95 (14 - 56)

31.00 ± 9.76 (14 - 52)

29.11 ± 10.19 (15 - 56)

0.432

slof_work

70

22.53 ± 4.85 (10 - 30)

22.51 ± 4.43 (15 - 30)

22.54 ± 5.30 (10 - 30)

0.981

slof_relationship

70

25.77 ± 6.02 (11 - 35)

25.37 ± 6.28 (13 - 35)

26.17 ± 5.81 (11 - 35)

0.582

satisfaction

70

20.81 ± 6.89 (5 - 32)

19.26 ± 6.62 (5 - 29)

22.37 ± 6.90 (5 - 32)

0.058

mhc_emotional

70

11.33 ± 3.82 (3 - 18)

10.89 ± 3.42 (3 - 17)

11.77 ± 4.19 (4 - 18)

0.336

mhc_social

70

15.11 ± 5.50 (6 - 30)

15.37 ± 5.56 (7 - 30)

14.86 ± 5.51 (6 - 26)

0.699

mhc_psychological

70

22.39 ± 6.11 (6 - 36)

21.94 ± 5.79 (10 - 36)

22.83 ± 6.47 (6 - 36)

0.548

resilisnce

70

16.63 ± 4.53 (6 - 27)

16.26 ± 4.37 (6 - 24)

17.00 ± 4.72 (7 - 27)

0.496

social_provision

70

13.71 ± 2.94 (5 - 20)

13.26 ± 2.56 (8 - 20)

14.17 ± 3.25 (5 - 20)

0.195

els_value_living

70

17.33 ± 2.95 (5 - 25)

16.66 ± 2.38 (12 - 22)

18.00 ± 3.33 (5 - 25)

0.056

els_life_fulfill

70

12.90 ± 3.27 (4 - 20)

11.89 ± 3.05 (5 - 17)

13.91 ± 3.21 (4 - 20)

0.008

els

70

30.23 ± 5.57 (9 - 45)

28.54 ± 4.45 (20 - 36)

31.91 ± 6.12 (9 - 45)

0.010

social_connect

70

26.76 ± 9.31 (8 - 48)

27.74 ± 8.25 (8 - 45)

25.77 ± 10.28 (8 - 48)

0.380

shs_agency

70

14.59 ± 4.93 (3 - 24)

13.89 ± 4.64 (3 - 21)

15.29 ± 5.18 (3 - 24)

0.238

shs_pathway

70

16.70 ± 3.95 (4 - 24)

16.23 ± 3.85 (8 - 24)

17.17 ± 4.04 (4 - 23)

0.321

shs

70

31.29 ± 8.40 (7 - 47)

30.11 ± 8.13 (13 - 45)

32.46 ± 8.62 (7 - 47)

0.246

esteem

70

12.70 ± 1.49 (10 - 18)

12.86 ± 1.57 (10 - 18)

12.54 ± 1.40 (10 - 16)

0.381

mlq_search

70

14.91 ± 3.38 (3 - 21)

14.80 ± 3.17 (6 - 21)

15.03 ± 3.63 (3 - 21)

0.780

mlq_presence

70

13.60 ± 4.13 (3 - 21)

13.51 ± 3.57 (5 - 20)

13.69 ± 4.67 (3 - 21)

0.864

mlq

70

28.51 ± 6.71 (6 - 42)

28.31 ± 5.95 (12 - 40)

28.71 ± 7.47 (6 - 42)

0.805

empower

70

19.60 ± 4.12 (6 - 28)

19.11 ± 3.82 (11 - 24)

20.09 ± 4.41 (6 - 28)

0.328

ismi_resistance

70

14.60 ± 2.70 (5 - 20)

14.31 ± 2.27 (11 - 19)

14.89 ± 3.08 (5 - 20)

0.380

ismi_discrimation

70

11.33 ± 3.24 (5 - 19)

12.26 ± 2.86 (5 - 18)

10.40 ± 3.37 (5 - 19)

0.015

sss_affective

70

10.00 ± 3.87 (3 - 18)

10.57 ± 3.49 (3 - 18)

9.43 ± 4.19 (3 - 18)

0.219

sss_behavior

70

9.70 ± 3.99 (3 - 18)

10.49 ± 3.97 (3 - 18)

8.91 ± 3.92 (3 - 18)

0.100

sss_cognitive

70

8.27 ± 4.01 (3 - 18)

8.66 ± 4.26 (3 - 18)

7.89 ± 3.77 (3 - 18)

0.425

sss

70

27.97 ± 11.03 (9 - 54)

29.71 ± 10.56 (9 - 54)

26.23 ± 11.36 (9 - 54)

0.188

1Mean ± SD (Range)

2Two Sample t-test

Plot

Data analysis

Table

Group

Characteristic

Beta

SE1

95% CI1

p-value

recovery_stage_a

(Intercept)

3.14

0.206

2.74, 3.55

group

control

—

—

—

treatment

0.000

0.291

-0.571, 0.571

1.00

time_point

1st

—

—

—

2nd

0.321

0.315

-0.296, 0.939

0.312

group * time_point

treatment * 2nd

0.028

0.436

-0.826, 0.883

0.948

Pseudo R square

0.017

recovery_stage_b

(Intercept)

17.9

0.456

17.0, 18.8

group

control

—

—

—

treatment

0.257

0.644

-1.01, 1.52

0.691

time_point

1st

—

—

—

2nd

-0.093

0.634

-1.34, 1.15

0.884

group * time_point

treatment * 2nd

0.567

0.876

-1.15, 2.28

0.521

Pseudo R square

0.011

ras_confidence

(Intercept)

29.7

0.843

28.1, 31.4

group

control

—

—

—

treatment

1.46

1.193

-0.880, 3.79

0.225

time_point

1st

—

—

—

2nd

0.339

0.908

-1.44, 2.12

0.711

group * time_point

treatment * 2nd

0.208

1.253

-2.25, 2.66

0.869

Pseudo R square

0.025

ras_willingness

(Intercept)

11.9

0.335

11.3, 12.6

group

control

—

—

—

treatment

0.257

0.474

-0.671, 1.19

0.589

time_point

1st

—

—

—

2nd

-0.826

0.327

-1.47, -0.186

0.015

group * time_point

treatment * 2nd

0.684

0.450

-0.199, 1.57

0.137

Pseudo R square

0.033

ras_goal

(Intercept)

17.5

0.531

16.5, 18.6

group

control

—

—

—

treatment

0.143

0.751

-1.33, 1.62

0.850

time_point

1st

—

—

—

2nd

-0.760

0.595

-1.93, 0.407

0.209

group * time_point

treatment * 2nd

1.33

0.821

-0.279, 2.94

0.113

Pseudo R square

0.019

ras_reliance

(Intercept)

12.9

0.472

12.0, 13.8

group

control

—

—

—

treatment

0.629

0.667

-0.679, 1.94

0.349

time_point

1st

—

—

—

2nd

0.238

0.422

-0.589, 1.06

0.576

group * time_point

treatment * 2nd

0.808

0.581

-0.332, 1.95

0.172

Pseudo R square

0.043

ras_domination

(Intercept)

10.4

0.365

9.71, 11.1

group

control

—

—

—

treatment

-0.829

0.516

-1.84, 0.183

0.112

time_point

1st

—

—

—

2nd

-0.391

0.488

-1.35, 0.564

0.426

group * time_point

treatment * 2nd

1.12

0.674

-0.203, 2.44

0.104

Pseudo R square

0.027

symptom

(Intercept)

31.0

1.678

27.7, 34.3

group

control

—

—

—

treatment

-1.89

2.374

-6.54, 2.77

0.430

time_point

1st

—

—

—

2nd

-0.451

1.173

-2.75, 1.85

0.703

group * time_point

treatment * 2nd

-0.233

1.616

-3.40, 2.93

0.886

Pseudo R square

0.011

slof_work

(Intercept)

22.5

0.831

20.9, 24.1

group

control

—

—

—

treatment

0.029

1.176

-2.28, 2.33

0.981

time_point

1st

—

—

—

2nd

-0.508

0.673

-1.83, 0.810

0.454

group * time_point

treatment * 2nd

-0.749

0.927

-2.57, 1.07

0.424

Pseudo R square

0.009

slof_relationship

(Intercept)

25.4

1.013

23.4, 27.4

group

control

—

—

—

treatment

0.800

1.432

-2.01, 3.61

0.578

time_point

1st

—

—

—

2nd

-1.42

0.957

-3.29, 0.459

0.147

group * time_point

treatment * 2nd

0.960

1.319

-1.63, 3.55

0.471

Pseudo R square

0.015

satisfaction

(Intercept)

19.3

1.178

16.9, 21.6

group

control

—

—

—

treatment

3.11

1.666

-0.151, 6.38

0.065

time_point

1st

—

—

—

2nd

0.706

1.329

-1.90, 3.31

0.598

group * time_point

treatment * 2nd

-1.21

1.833

-4.81, 2.38

0.512

Pseudo R square

0.038

mhc_emotional

(Intercept)

10.9

0.640

9.63, 12.1

group

control

—

—

—

treatment

0.886

0.905

-0.888, 2.66

0.331

time_point

1st

—

—

—

2nd

0.489

0.592

-0.671, 1.65

0.414

group * time_point

treatment * 2nd

-1.18

0.816

-2.78, 0.418

0.156

Pseudo R square

0.010

mhc_social

(Intercept)

15.4

0.954

13.5, 17.2

group

control

—

—

—

treatment

-0.514

1.349

-3.16, 2.13

0.704

time_point

1st

—

—

—

2nd

0.988

0.984

-0.940, 2.92

0.321

group * time_point

treatment * 2nd

-1.52

1.357

-4.18, 1.14

0.269

Pseudo R square

0.013

mhc_psychological

(Intercept)

21.9

1.073

19.8, 24.0

group

control

—

—

—

treatment

0.886

1.518

-2.09, 3.86

0.561

time_point

1st

—

—

—

2nd

0.579

1.119

-1.61, 2.77

0.608

group * time_point

treatment * 2nd

-1.64

1.543

-4.67, 1.38

0.293

Pseudo R square

0.005

resilisnce

(Intercept)

16.3

0.734

14.8, 17.7

group

control

—

—

—

treatment

0.743

1.038

-1.29, 2.78

0.476

time_point

1st

—

—

—

2nd

0.336

0.731

-1.10, 1.77

0.648

group * time_point

treatment * 2nd

0.175

1.009

-1.80, 2.15

0.863

Pseudo R square

0.011

social_provision

(Intercept)

13.3

0.489

12.3, 14.2

group

control

—

—

—

treatment

0.914

0.691

-0.440, 2.27

0.189

time_point

1st

—

—

—

2nd

-0.400

0.523

-1.42, 0.626

0.449

group * time_point

treatment * 2nd

0.327

0.722

-1.09, 1.74

0.653

Pseudo R square

0.032

els_value_living

(Intercept)

16.7

0.492

15.7, 17.6

group

control

—

—

—

treatment

1.34

0.696

-0.020, 2.71

0.057

time_point

1st

—

—

—

2nd

0.403

0.501

-0.579, 1.38

0.426

group * time_point

treatment * 2nd

-0.363

0.691

-1.72, 0.991

0.602

Pseudo R square

0.045

els_life_fulfill

(Intercept)

11.9

0.515

10.9, 12.9

group

control

—

—

—

treatment

2.03

0.728

0.601, 3.46

0.007

time_point

1st

—

—

—

2nd

0.966

0.547

-0.105, 2.04

0.085

group * time_point

treatment * 2nd

-0.993

0.754

-2.47, 0.484

0.195

Pseudo R square

0.082

els

(Intercept)

28.5

0.901

26.8, 30.3

group

control

—

—

—

treatment

3.37

1.275

0.873, 5.87

0.010

time_point

1st

—

—

—

2nd

1.31

0.865

-0.390, 3.00

0.139

group * time_point

treatment * 2nd

-1.28

1.192

-3.61, 1.06

0.291

Pseudo R square

0.077

social_connect

(Intercept)

27.7

1.541

24.7, 30.8

group

control

—

—

—

treatment

-1.97

2.179

-6.24, 2.30

0.369

time_point

1st

—

—

—

2nd

0.190

1.249

-2.26, 2.64

0.880

group * time_point

treatment * 2nd

-0.292

1.721

-3.67, 3.08

0.866

Pseudo R square

0.013

shs_agency

(Intercept)

13.9

0.830

12.3, 15.5

group

control

—

—

—

treatment

1.40

1.173

-0.900, 3.70

0.237

time_point

1st

—

—

—

2nd

0.136

0.788

-1.41, 1.68

0.864

group * time_point

treatment * 2nd

0.565

1.087

-1.57, 2.70

0.606

Pseudo R square

0.029

shs_pathway

(Intercept)

16.2

0.656

14.9, 17.5

group

control

—

—

—

treatment

0.943

0.928

-0.876, 2.76

0.313

time_point

1st

—

—

—

2nd

0.462

0.564

-0.644, 1.57

0.418

group * time_point

treatment * 2nd

-0.530

0.778

-2.05, 0.994

0.500

Pseudo R square

0.011

shs

(Intercept)

30.1

1.400

27.4, 32.9

group

control

—

—

—

treatment

2.34

1.979

-1.54, 6.22

0.240

time_point

1st

—

—

—

2nd

0.568

1.195

-1.77, 2.91

0.637

group * time_point

treatment * 2nd

0.094

1.647

-3.13, 3.32

0.955

Pseudo R square

0.022

esteem

(Intercept)

12.9

0.237

12.4, 13.3

group

control

—

—

—

treatment

-0.314

0.335

-0.971, 0.342

0.351

time_point

1st

—

—

—

2nd

0.198

0.394

-0.575, 0.971

0.618

group * time_point

treatment * 2nd

0.040

0.547

-1.03, 1.11

0.941

Pseudo R square

0.016

mlq_search

(Intercept)

14.8

0.575

13.7, 15.9

group

control

—

—

—

treatment

0.229

0.813

-1.37, 1.82

0.779

time_point

1st

—

—

—

2nd

-0.106

0.741

-1.56, 1.35

0.887

group * time_point

treatment * 2nd

0.068

1.023

-1.94, 2.07

0.947

Pseudo R square

0.001

mlq_presence

(Intercept)

13.5

0.683

12.2, 14.9

group

control

—

—

—

treatment

0.171

0.967

-1.72, 2.07

0.860

time_point

1st

—

—

—

2nd

0.031

0.819

-1.57, 1.64

0.970

group * time_point

treatment * 2nd

0.020

1.131

-2.20, 2.24

0.986

Pseudo R square

0.001

mlq

(Intercept)

28.3

1.144

26.1, 30.6

group

control

—

—

—

treatment

0.400

1.618

-2.77, 3.57

0.805

time_point

1st

—

—

—

2nd

-0.093

1.400

-2.84, 2.65

0.948

group * time_point

treatment * 2nd

0.097

1.933

-3.69, 3.89

0.960

Pseudo R square

0.001

empower

(Intercept)

19.1

0.671

17.8, 20.4

group

control

—

—

—

treatment

0.971

0.949

-0.889, 2.83

0.309

time_point

1st

—

—

—

2nd

0.158

0.642

-1.10, 1.42

0.807

group * time_point

treatment * 2nd

-0.869

0.885

-2.60, 0.865

0.332

Pseudo R square

0.011

ismi_resistance

(Intercept)

14.3

0.429

13.5, 15.2

group

control

—

—

—

treatment

0.571

0.607

-0.619, 1.76

0.349

time_point

1st

—

—

—

2nd

0.436

0.609

-0.758, 1.63

0.478

group * time_point

treatment * 2nd

-0.566

0.842

-2.22, 1.08

0.505

Pseudo R square

0.009

ismi_discrimation

(Intercept)

12.3

0.537

11.2, 13.3

group

control

—

—

—

treatment

-1.86

0.759

-3.34, -0.369

0.017

time_point

1st

—

—

—

2nd

-0.865

0.545

-1.93, 0.202

0.120

group * time_point

treatment * 2nd

1.28

0.751

-0.195, 2.75

0.097

Pseudo R square

0.058

sss_affective

(Intercept)

10.6

0.630

9.34, 11.8

group

control

—

—

—

treatment

-1.14

0.891

-2.89, 0.604

0.204

time_point

1st

—

—

—

2nd

-0.040

0.546

-1.11, 1.03

0.943

group * time_point

treatment * 2nd

-0.820

0.753

-2.30, 0.655

0.283

Pseudo R square

0.042

sss_behavior

(Intercept)

10.5

0.646

9.22, 11.8

group

control

—

—

—

treatment

-1.57

0.914

-3.36, 0.220

0.090

time_point

1st

—

—

—

2nd

-0.069

0.616

-1.28, 1.14

0.911

group * time_point

treatment * 2nd

-0.641

0.850

-2.31, 1.02

0.455

Pseudo R square

0.057

sss_cognitive

(Intercept)

8.66

0.666

7.35, 9.96

group

control

—

—

—

treatment

-0.771

0.942

-2.62, 1.08

0.416

time_point

1st

—

—

—

2nd

0.891

0.555

-0.196, 1.98

0.116

group * time_point

treatment * 2nd

-1.67

0.764

-3.17, -0.172

0.035

Pseudo R square

0.038

sss

(Intercept)

29.7

1.800

26.2, 33.2

group

control

—

—

—

treatment

-3.49

2.546

-8.48, 1.50

0.175

time_point

1st

—

—

—

2nd

0.857

1.427

-1.94, 3.65

0.552

group * time_point

treatment * 2nd

-3.16

1.967

-7.02, 0.695

0.116

Pseudo R square

0.050

1SE = Standard Error, CI = Confidence Interval

Text

recovery_stage_a

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict recovery_stage_a with group and time_point (formula: recovery_stage_a ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.32) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.14 (95% CI [2.74, 3.55], t(100) = 15.25, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 3.95e-15, 95% CI [-0.57, 0.57], t(100) = 1.36e-14, p > .999; Std. beta = -1.19e-16, 95% CI [-0.47, 0.47])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.32, 95% CI [-0.30, 0.94], t(100) = 1.02, p = 0.308; Std. beta = 0.26, 95% CI [-0.24, 0.77])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.03, 95% CI [-0.83, 0.88], t(100) = 0.07, p = 0.948; Std. beta = 0.02, 95% CI [-0.68, 0.73])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

recovery_stage_b

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict recovery_stage_b with group and time_point (formula: recovery_stage_b ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.46) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 17.86 (95% CI [16.96, 18.75], t(100) = 39.19, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.26, 95% CI [-1.01, 1.52], t(100) = 0.40, p = 0.690; Std. beta = 0.10, 95% CI [-0.37, 0.57])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.09, 95% CI [-1.34, 1.15], t(100) = -0.15, p = 0.883; Std. beta = -0.03, 95% CI [-0.50, 0.43])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.57, 95% CI [-1.15, 2.28], t(100) = 0.65, p = 0.518; Std. beta = 0.21, 95% CI [-0.43, 0.85])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_confidence

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_confidence with group and time_point (formula: ras_confidence ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 29.71 (95% CI [28.06, 31.37], t(100) = 35.24, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.46, 95% CI [-0.88, 3.79], t(100) = 1.22, p = 0.222; Std. beta = 0.29, 95% CI [-0.18, 0.76])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.34, 95% CI [-1.44, 2.12], t(100) = 0.37, p = 0.709; Std. beta = 0.07, 95% CI [-0.29, 0.43])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.21, 95% CI [-2.25, 2.66], t(100) = 0.17, p = 0.868; Std. beta = 0.04, 95% CI [-0.45, 0.54])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_willingness

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_willingness with group and time_point (formula: ras_willingness ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.76) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.94 (95% CI [11.29, 12.60], t(100) = 35.65, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.26, 95% CI [-0.67, 1.19], t(100) = 0.54, p = 0.587; Std. beta = 0.13, 95% CI [-0.34, 0.60])
  • The effect of time point [2nd] is statistically significant and negative (beta = -0.83, 95% CI [-1.47, -0.19], t(100) = -2.53, p = 0.011; Std. beta = -0.42, 95% CI [-0.74, -0.09])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.68, 95% CI [-0.20, 1.57], t(100) = 1.52, p = 0.129; Std. beta = 0.35, 95% CI [-0.10, 0.79])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_goal

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_goal with group and time_point (formula: ras_goal ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.67) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 17.51 (95% CI [16.47, 18.56], t(100) = 32.96, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.14, 95% CI [-1.33, 1.62], t(100) = 0.19, p = 0.849; Std. beta = 0.05, 95% CI [-0.42, 0.51])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.76, 95% CI [-1.93, 0.41], t(100) = -1.28, p = 0.202; Std. beta = -0.24, 95% CI [-0.61, 0.13])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.33, 95% CI [-0.28, 2.94], t(100) = 1.62, p = 0.105; Std. beta = 0.42, 95% CI [-0.09, 0.93])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_reliance

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_reliance with group and time_point (formula: ras_reliance ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.80) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.89 (95% CI [11.96, 13.81], t(100) = 27.33, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.63, 95% CI [-0.68, 1.94], t(100) = 0.94, p = 0.346; Std. beta = 0.22, 95% CI [-0.23, 0.67])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.24, 95% CI [-0.59, 1.06], t(100) = 0.56, p = 0.573; Std. beta = 0.08, 95% CI [-0.20, 0.37])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.81, 95% CI [-0.33, 1.95], t(100) = 1.39, p = 0.165; Std. beta = 0.28, 95% CI [-0.11, 0.67])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_domination

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_domination with group and time_point (formula: ras_domination ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.52) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 10.43 (95% CI [9.71, 11.14], t(100) = 28.59, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.83, 95% CI [-1.84, 0.18], t(100) = -1.61, p = 0.108; Std. beta = -0.38, 95% CI [-0.85, 0.08])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.39, 95% CI [-1.35, 0.56], t(100) = -0.80, p = 0.422; Std. beta = -0.18, 95% CI [-0.62, 0.26])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.12, 95% CI [-0.20, 2.44], t(100) = 1.66, p = 0.097; Std. beta = 0.52, 95% CI [-0.09, 1.13])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

symptom

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict symptom with group and time_point (formula: symptom ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.88) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 31.00 (95% CI [27.71, 34.29], t(100) = 18.47, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -1.89, 95% CI [-6.54, 2.77], t(100) = -0.79, p = 0.427; Std. beta = -0.19, 95% CI [-0.65, 0.28])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.45, 95% CI [-2.75, 1.85], t(100) = -0.38, p = 0.700; Std. beta = -0.04, 95% CI [-0.27, 0.18])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.23, 95% CI [-3.40, 2.93], t(100) = -0.14, p = 0.885; Std. beta = -0.02, 95% CI [-0.34, 0.29])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

slof_work

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict slof_work with group and time_point (formula: slof_work ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.84) and the part related to the fixed effects alone (marginal R2) is of 9.37e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 22.51 (95% CI [20.88, 24.14], t(100) = 27.08, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.03, 95% CI [-2.28, 2.33], t(100) = 0.02, p = 0.981; Std. beta = 5.80e-03, 95% CI [-0.46, 0.47])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.51, 95% CI [-1.83, 0.81], t(100) = -0.76, p = 0.450; Std. beta = -0.10, 95% CI [-0.37, 0.16])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.75, 95% CI [-2.57, 1.07], t(100) = -0.81, p = 0.419; Std. beta = -0.15, 95% CI [-0.52, 0.22])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

slof_relationship

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict slof_relationship with group and time_point (formula: slof_relationship ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.77) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 25.37 (95% CI [23.39, 27.36], t(100) = 25.05, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.80, 95% CI [-2.01, 3.61], t(100) = 0.56, p = 0.577; Std. beta = 0.14, 95% CI [-0.35, 0.62])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -1.42, 95% CI [-3.29, 0.46], t(100) = -1.48, p = 0.139; Std. beta = -0.24, 95% CI [-0.57, 0.08])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.96, 95% CI [-1.63, 3.55], t(100) = 0.73, p = 0.467; Std. beta = 0.17, 95% CI [-0.28, 0.61])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

satisfaction

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict satisfaction with group and time_point (formula: satisfaction ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.67) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 19.26 (95% CI [16.95, 21.57], t(100) = 16.35, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 3.11, 95% CI [-0.15, 6.38], t(100) = 1.87, p = 0.062; Std. beta = 0.44, 95% CI [-0.02, 0.91])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.71, 95% CI [-1.90, 3.31], t(100) = 0.53, p = 0.595; Std. beta = 0.10, 95% CI [-0.27, 0.47])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.21, 95% CI [-4.81, 2.38], t(100) = -0.66, p = 0.509; Std. beta = -0.17, 95% CI [-0.68, 0.34])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mhc_emotional

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mhc_emotional with group and time_point (formula: mhc_emotional ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.78) and the part related to the fixed effects alone (marginal R2) is of 9.74e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 10.89 (95% CI [9.63, 12.14], t(100) = 17.01, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.89, 95% CI [-0.89, 2.66], t(100) = 0.98, p = 0.328; Std. beta = 0.24, 95% CI [-0.24, 0.72])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.49, 95% CI [-0.67, 1.65], t(100) = 0.83, p = 0.409; Std. beta = 0.13, 95% CI [-0.18, 0.45])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.18, 95% CI [-2.78, 0.42], t(100) = -1.45, p = 0.148; Std. beta = -0.32, 95% CI [-0.75, 0.11])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mhc_social

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mhc_social with group and time_point (formula: mhc_social ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.73) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.37 (95% CI [13.50, 17.24], t(100) = 16.11, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.51, 95% CI [-3.16, 2.13], t(100) = -0.38, p = 0.703; Std. beta = -0.09, 95% CI [-0.57, 0.39])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.99, 95% CI [-0.94, 2.92], t(100) = 1.00, p = 0.315; Std. beta = 0.18, 95% CI [-0.17, 0.53])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.52, 95% CI [-4.18, 1.14], t(100) = -1.12, p = 0.262; Std. beta = -0.28, 95% CI [-0.76, 0.21])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mhc_psychological

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mhc_psychological with group and time_point (formula: mhc_psychological ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.72) and the part related to the fixed effects alone (marginal R2) is of 4.83e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 21.94 (95% CI [19.84, 24.05], t(100) = 20.45, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.89, 95% CI [-2.09, 3.86], t(100) = 0.58, p = 0.559; Std. beta = 0.14, 95% CI [-0.33, 0.61])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.58, 95% CI [-1.61, 2.77], t(100) = 0.52, p = 0.605; Std. beta = 0.09, 95% CI [-0.26, 0.44])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.64, 95% CI [-4.67, 1.38], t(100) = -1.06, p = 0.287; Std. beta = -0.26, 95% CI [-0.74, 0.22])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

resilisnce

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict resilisnce with group and time_point (formula: resilisnce ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.74) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 16.26 (95% CI [14.82, 17.70], t(100) = 22.16, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.74, 95% CI [-1.29, 2.78], t(100) = 0.72, p = 0.474; Std. beta = 0.17, 95% CI [-0.30, 0.64])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.34, 95% CI [-1.10, 1.77], t(100) = 0.46, p = 0.646; Std. beta = 0.08, 95% CI [-0.25, 0.41])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.17, 95% CI [-1.80, 2.15], t(100) = 0.17, p = 0.862; Std. beta = 0.04, 95% CI [-0.42, 0.50])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

social_provision

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict social_provision with group and time_point (formula: social_provision ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.26 (95% CI [12.30, 14.21], t(100) = 27.14, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.91, 95% CI [-0.44, 2.27], t(100) = 1.32, p = 0.186; Std. beta = 0.31, 95% CI [-0.15, 0.77])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.40, 95% CI [-1.42, 0.63], t(100) = -0.76, p = 0.445; Std. beta = -0.14, 95% CI [-0.49, 0.21])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.33, 95% CI [-1.09, 1.74], t(100) = 0.45, p = 0.650; Std. beta = 0.11, 95% CI [-0.37, 0.59])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

els_value_living

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict els_value_living with group and time_point (formula: els_value_living ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.74) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 16.66 (95% CI [15.69, 17.62], t(100) = 33.87, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.34, 95% CI [-0.02, 2.71], t(100) = 1.93, p = 0.054; Std. beta = 0.45, 95% CI [-6.87e-03, 0.91])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.40, 95% CI [-0.58, 1.38], t(100) = 0.80, p = 0.421; Std. beta = 0.14, 95% CI [-0.19, 0.47])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.36, 95% CI [-1.72, 0.99], t(100) = -0.53, p = 0.599; Std. beta = -0.12, 95% CI [-0.58, 0.33])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

els_life_fulfill

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict els_life_fulfill with group and time_point (formula: els_life_fulfill ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.73) and the part related to the fixed effects alone (marginal R2) is of 0.08. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.89 (95% CI [10.88, 12.90], t(100) = 23.08, p < .001). Within this model:

  • The effect of group [treatment] is statistically significant and positive (beta = 2.03, 95% CI [0.60, 3.46], t(100) = 2.78, p = 0.005; Std. beta = 0.65, 95% CI [0.19, 1.11])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.97, 95% CI [-0.11, 2.04], t(100) = 1.77, p = 0.077; Std. beta = 0.31, 95% CI [-0.03, 0.65])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.99, 95% CI [-2.47, 0.48], t(100) = -1.32, p = 0.188; Std. beta = -0.32, 95% CI [-0.79, 0.16])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

els

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict els with group and time_point (formula: els ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.78) and the part related to the fixed effects alone (marginal R2) is of 0.08. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.54 (95% CI [26.78, 30.31], t(100) = 31.67, p < .001). Within this model:

  • The effect of group [treatment] is statistically significant and positive (beta = 3.37, 95% CI [0.87, 5.87], t(100) = 2.64, p = 0.008; Std. beta = 0.61, 95% CI [0.16, 1.06])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 1.31, 95% CI [-0.39, 3.00], t(100) = 1.51, p = 0.131; Std. beta = 0.24, 95% CI [-0.07, 0.54])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.28, 95% CI [-3.61, 1.06], t(100) = -1.07, p = 0.284; Std. beta = -0.23, 95% CI [-0.65, 0.19])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

social_connect

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict social_connect with group and time_point (formula: social_connect ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.84) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 27.74 (95% CI [24.72, 30.76], t(100) = 18.00, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -1.97, 95% CI [-6.24, 2.30], t(100) = -0.90, p = 0.366; Std. beta = -0.21, 95% CI [-0.68, 0.25])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.19, 95% CI [-2.26, 2.64], t(100) = 0.15, p = 0.879; Std. beta = 0.02, 95% CI [-0.25, 0.29])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.29, 95% CI [-3.67, 3.08], t(100) = -0.17, p = 0.865; Std. beta = -0.03, 95% CI [-0.40, 0.33])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

shs_agency

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict shs_agency with group and time_point (formula: shs_agency ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.77) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.89 (95% CI [12.26, 15.51], t(100) = 16.73, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.40, 95% CI [-0.90, 3.70], t(100) = 1.19, p = 0.233; Std. beta = 0.29, 95% CI [-0.18, 0.76])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.14, 95% CI [-1.41, 1.68], t(100) = 0.17, p = 0.863; Std. beta = 0.03, 95% CI [-0.29, 0.35])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.57, 95% CI [-1.57, 2.70], t(100) = 0.52, p = 0.603; Std. beta = 0.12, 95% CI [-0.32, 0.55])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

shs_pathway

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict shs_pathway with group and time_point (formula: shs_pathway ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.81) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 16.23 (95% CI [14.94, 17.51], t(100) = 24.73, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.94, 95% CI [-0.88, 2.76], t(100) = 1.02, p = 0.310; Std. beta = 0.25, 95% CI [-0.23, 0.73])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.46, 95% CI [-0.64, 1.57], t(100) = 0.82, p = 0.413; Std. beta = 0.12, 95% CI [-0.17, 0.42])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.53, 95% CI [-2.05, 0.99], t(100) = -0.68, p = 0.496; Std. beta = -0.14, 95% CI [-0.55, 0.26])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

shs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict shs with group and time_point (formula: shs ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.82) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 30.11 (95% CI [27.37, 32.86], t(100) = 21.52, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 2.34, 95% CI [-1.54, 6.22], t(100) = 1.18, p = 0.237; Std. beta = 0.29, 95% CI [-0.19, 0.77])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.57, 95% CI [-1.77, 2.91], t(100) = 0.48, p = 0.634; Std. beta = 0.07, 95% CI [-0.22, 0.36])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.09, 95% CI [-3.13, 3.32], t(100) = 0.06, p = 0.955; Std. beta = 0.01, 95% CI [-0.39, 0.41])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

esteem

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict esteem with group and time_point (formula: esteem ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is moderate (conditional R2 = 0.15) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.86 (95% CI [12.39, 13.32], t(100) = 54.27, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.31, 95% CI [-0.97, 0.34], t(100) = -0.94, p = 0.348; Std. beta = -0.23, 95% CI [-0.70, 0.25])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.20, 95% CI [-0.57, 0.97], t(100) = 0.50, p = 0.615; Std. beta = 0.14, 95% CI [-0.41, 0.70])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.04, 95% CI [-1.03, 1.11], t(100) = 0.07, p = 0.941; Std. beta = 0.03, 95% CI [-0.74, 0.80])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mlq_search

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mlq_search with group and time_point (formula: mlq_search ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.54) and the part related to the fixed effects alone (marginal R2) is of 1.48e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.80 (95% CI [13.67, 15.93], t(100) = 25.74, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.23, 95% CI [-1.37, 1.82], t(100) = 0.28, p = 0.779; Std. beta = 0.07, 95% CI [-0.41, 0.55])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.11, 95% CI [-1.56, 1.35], t(100) = -0.14, p = 0.887; Std. beta = -0.03, 95% CI [-0.47, 0.40])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.07, 95% CI [-1.94, 2.07], t(100) = 0.07, p = 0.947; Std. beta = 0.02, 95% CI [-0.58, 0.62])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mlq_presence

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mlq_presence with group and time_point (formula: mlq_presence ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.61) and the part related to the fixed effects alone (marginal R2) is of 5.19e-04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.51 (95% CI [12.17, 14.85], t(100) = 19.77, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.17, 95% CI [-1.72, 2.07], t(100) = 0.18, p = 0.859; Std. beta = 0.04, 95% CI [-0.43, 0.52])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.03, 95% CI [-1.57, 1.64], t(100) = 0.04, p = 0.970; Std. beta = 7.71e-03, 95% CI [-0.40, 0.41])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.02, 95% CI [-2.20, 2.24], t(100) = 0.02, p = 0.986; Std. beta = 4.92e-03, 95% CI [-0.55, 0.56])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mlq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mlq with group and time_point (formula: mlq ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.59) and the part related to the fixed effects alone (marginal R2) is of 1.05e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.31 (95% CI [26.07, 30.56], t(100) = 24.76, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.40, 95% CI [-2.77, 3.57], t(100) = 0.25, p = 0.805; Std. beta = 0.06, 95% CI [-0.42, 0.54])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.09, 95% CI [-2.84, 2.65], t(100) = -0.07, p = 0.947; Std. beta = -0.01, 95% CI [-0.43, 0.40])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.10, 95% CI [-3.69, 3.89], t(100) = 0.05, p = 0.960; Std. beta = 0.01, 95% CI [-0.55, 0.58])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

empower

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict empower with group and time_point (formula: empower ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.77) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 19.11 (95% CI [17.80, 20.43], t(100) = 28.48, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.97, 95% CI [-0.89, 2.83], t(100) = 1.02, p = 0.306; Std. beta = 0.25, 95% CI [-0.23, 0.72])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.16, 95% CI [-1.10, 1.42], t(100) = 0.25, p = 0.805; Std. beta = 0.04, 95% CI [-0.28, 0.36])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.87, 95% CI [-2.60, 0.87], t(100) = -0.98, p = 0.326; Std. beta = -0.22, 95% CI [-0.66, 0.22])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ismi_resistance

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ismi_resistance with group and time_point (formula: ismi_resistance ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.43) and the part related to the fixed effects alone (marginal R2) is of 9.17e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.31 (95% CI [13.47, 15.16], t(100) = 33.34, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.57, 95% CI [-0.62, 1.76], t(100) = 0.94, p = 0.347; Std. beta = 0.23, 95% CI [-0.25, 0.70])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.44, 95% CI [-0.76, 1.63], t(100) = 0.72, p = 0.474; Std. beta = 0.17, 95% CI [-0.30, 0.65])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.57, 95% CI [-2.22, 1.08], t(100) = -0.67, p = 0.502; Std. beta = -0.22, 95% CI [-0.88, 0.43])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ismi_discrimation

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ismi_discrimation with group and time_point (formula: ismi_discrimation ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.75) and the part related to the fixed effects alone (marginal R2) is of 0.06. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.26 (95% CI [11.21, 13.31], t(100) = 22.84, p < .001). Within this model:

  • The effect of group [treatment] is statistically significant and negative (beta = -1.86, 95% CI [-3.34, -0.37], t(100) = -2.45, p = 0.014; Std. beta = -0.58, 95% CI [-1.04, -0.11])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.87, 95% CI [-1.93, 0.20], t(100) = -1.59, p = 0.112; Std. beta = -0.27, 95% CI [-0.60, 0.06])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.28, 95% CI [-0.19, 2.75], t(100) = 1.70, p = 0.089; Std. beta = 0.40, 95% CI [-0.06, 0.85])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

sss_affective

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sss_affective with group and time_point (formula: sss_affective ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.82) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 10.57 (95% CI [9.34, 11.81], t(100) = 16.78, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -1.14, 95% CI [-2.89, 0.60], t(100) = -1.28, p = 0.200; Std. beta = -0.30, 95% CI [-0.75, 0.16])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.04, 95% CI [-1.11, 1.03], t(100) = -0.07, p = 0.942; Std. beta = -0.01, 95% CI [-0.29, 0.27])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.82, 95% CI [-2.30, 0.66], t(100) = -1.09, p = 0.276; Std. beta = -0.21, 95% CI [-0.60, 0.17])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

sss_behavior

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sss_behavior with group and time_point (formula: sss_behavior ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.78) and the part related to the fixed effects alone (marginal R2) is of 0.06. The model’s intercept, corresponding to group = control and time_point = 1st, is at 10.49 (95% CI [9.22, 11.75], t(100) = 16.22, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -1.57, 95% CI [-3.36, 0.22], t(100) = -1.72, p = 0.086; Std. beta = -0.40, 95% CI [-0.85, 0.06])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.07, 95% CI [-1.28, 1.14], t(100) = -0.11, p = 0.911; Std. beta = -0.02, 95% CI [-0.32, 0.29])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.64, 95% CI [-2.31, 1.02], t(100) = -0.75, p = 0.450; Std. beta = -0.16, 95% CI [-0.59, 0.26])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

sss_cognitive

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sss_cognitive with group and time_point (formula: sss_cognitive ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.83) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 8.66 (95% CI [7.35, 9.96], t(100) = 12.99, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.77, 95% CI [-2.62, 1.08], t(100) = -0.82, p = 0.413; Std. beta = -0.20, 95% CI [-0.67, 0.27])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.89, 95% CI [-0.20, 1.98], t(100) = 1.61, p = 0.108; Std. beta = 0.23, 95% CI [-0.05, 0.50])
  • The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -1.67, 95% CI [-3.17, -0.17], t(100) = -2.18, p = 0.029; Std. beta = -0.43, 95% CI [-0.81, -0.04])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

sss

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sss with group and time_point (formula: sss ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.85) and the part related to the fixed effects alone (marginal R2) is of 0.05. The model’s intercept, corresponding to group = control and time_point = 1st, is at 29.71 (95% CI [26.19, 33.24], t(100) = 16.51, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -3.49, 95% CI [-8.48, 1.50], t(100) = -1.37, p = 0.171; Std. beta = -0.32, 95% CI [-0.77, 0.14])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.86, 95% CI [-1.94, 3.65], t(100) = 0.60, p = 0.548; Std. beta = 0.08, 95% CI [-0.18, 0.33])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -3.16, 95% CI [-7.02, 0.70], t(100) = -1.61, p = 0.108; Std. beta = -0.29, 95% CI [-0.64, 0.06])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

Likelihood ratio tests

outcome

model

npar

AIC

BIC

logLik

deviance

Chisq

Df

p

recovery_stage_a

null

3

343.533

351.523

-168.766

337.533

recovery_stage_a

random

6

347.093

363.073

-167.546

335.093

2.440

3

0.486

recovery_stage_b

null

3

505.906

513.896

-249.953

499.906

recovery_stage_b

random

6

510.699

526.680

-249.349

498.699

1.207

3

0.751

ras_confidence

null

3

622.166

630.156

-308.083

616.166

ras_confidence

random

6

625.773

641.754

-306.886

613.773

2.393

3

0.495

ras_willingness

null

3

424.454

432.445

-209.227

418.454

ras_willingness

random

6

423.532

439.512

-205.766

411.532

6.923

3

0.074

ras_goal

null

3

527.593

535.583

-260.796

521.593

ras_goal

random

6

530.363

546.343

-259.181

518.363

3.230

3

0.357

ras_reliance

null

3

493.067

501.058

-243.534

487.067

ras_reliance

random

6

490.268

506.248

-239.134

478.268

8.800

3

0.032

ras_domination

null

3

459.561

467.552

-226.781

453.561

ras_domination

random

6

461.346

477.327

-224.673

449.346

4.215

3

0.239

symptom

null

3

737.752

745.742

-365.876

731.752

symptom

random

6

742.471

758.451

-365.235

730.471

1.281

3

0.734

slof_work

null

3

602.074

610.064

-298.037

596.074

slof_work

random

6

603.656

619.637

-295.828

591.656

4.418

3

0.220

slof_relationship

null

3

652.972

660.962

-323.486

646.972

slof_relationship

random

6

656.011

671.991

-322.005

644.011

2.962

3

0.398

satisfaction

null

3

697.153

705.143

-345.576

691.153

satisfaction

random

6

699.594

715.575

-343.797

687.594

3.559

3

0.313

mhc_emotional

null

3

553.895

561.886

-273.948

547.895

mhc_emotional

random

6

557.224

573.205

-272.612

545.224

2.671

3

0.445

mhc_social

null

3

645.041

653.031

-319.520

639.041

mhc_social

random

6

649.137

665.117

-318.568

637.137

1.904

3

0.593

mhc_psychological

null

3

670.173

678.163

-332.086

664.173

mhc_psychological

random

6

674.771

690.752

-331.386

662.771

1.402

3

0.705

resilisnce

null

3

586.671

594.661

-290.336

580.671

resilisnce

random

6

591.225

607.205

-289.612

579.225

1.446

3

0.695

social_provision

null

3

506.624

514.614

-250.312

500.624

social_provision

random

6

509.665

525.645

-248.832

497.665

2.959

3

0.398

els_value_living

null

3

506.045

514.035

-250.023

500.045

els_value_living

random

6

507.850

523.831

-247.925

495.850

4.195

3

0.241

els_life_fulfill

null

3

523.714

531.704

-258.857

517.714

els_life_fulfill

random

6

520.307

536.287

-254.153

508.307

9.407

3

0.024

els

null

3

634.614

642.604

-314.307

628.614

els

random

6

632.306

648.287

-310.153

620.306

8.308

3

0.040

social_connect

null

3

729.580

737.570

-361.790

723.580

social_connect

random

6

734.595

750.576

-361.298

722.595

0.984

3

0.805

shs_agency

null

3

611.007

618.997

-302.504

605.007

shs_agency

random

6

614.120

630.101

-301.060

602.120

2.887

3

0.409

shs_pathway

null

3

553.139

561.129

-273.570

547.139

shs_pathway

random

6

557.618

573.599

-272.809

545.618

1.521

3

0.677

shs

null

3

713.885

721.875

-353.942

707.885

shs

random

6

717.734

733.715

-352.867

705.734

2.150

3

0.542

esteem

null

3

375.439

383.429

-184.720

369.439

esteem

random

6

379.654

395.635

-183.827

367.654

1.785

3

0.618

mlq_search

null

3

549.829

557.819

-271.914

543.829

mlq_search

random

6

555.693

571.673

-271.846

543.693

0.136

3

0.987

mlq_presence

null

3

582.013

590.003

-288.006

576.013

mlq_presence

random

6

587.966

603.947

-287.983

575.966

0.047

3

0.997

mlq

null

3

692.518

700.509

-343.259

686.518

mlq

random

6

698.430

714.411

-343.215

686.430

0.088

3

0.993

empower

null

3

565.717

573.707

-279.858

559.717

empower

random

6

569.605

585.586

-278.802

557.605

2.112

3

0.550

ismi_resistance

null

3

494.246

502.236

-244.123

488.246

ismi_resistance

random

6

499.117

515.098

-243.559

487.117

1.129

3

0.770

ismi_discrimation

null

3

527.601

535.591

-260.800

521.601

ismi_discrimation

random

6

526.130

542.111

-257.065

514.130

7.470

3

0.058

sss_affective

null

3

548.923

556.913

-271.461

542.923

sss_affective

random

6

549.578

565.558

-268.789

537.578

5.345

3

0.148

sss_behavior

null

3

560.876

568.866

-277.438

554.876

sss_behavior

random

6

561.402

577.382

-274.701

549.402

5.474

3

0.140

sss_cognitive

null

3

559.076

567.066

-276.538

553.076

sss_cognitive

random

6

558.651

574.632

-273.326

546.651

6.425

3

0.093

sss

null

3

766.413

774.404

-380.207

760.413

sss

random

6

766.048

782.029

-377.024

754.048

6.365

3

0.095

Post hoc analysis

Table

outcome

time

control

treatment

between

n

estimate

within es

n

estimate

within es

p

es

recovery_stage_a

1st

35

3.14 ± 1.22

35

3.14 ± 1.22

1.000

0.000

recovery_stage_a

2nd

17

3.46 ± 1.20

-0.317

19

3.49 ± 1.21

-0.345

0.944

-0.028

recovery_stage_b

1st

35

17.86 ± 2.70

35

18.11 ± 2.70

0.691

-0.129

recovery_stage_b

2nd

17

17.76 ± 2.57

0.047

19

18.59 ± 2.59

-0.238

0.341

-0.413

ras_confidence

1st

35

29.71 ± 4.99

35

31.17 ± 4.99

0.225

-0.528

ras_confidence

2nd

17

30.05 ± 4.35

-0.123

19

31.72 ± 4.42

-0.198

0.258

-0.604

ras_willingness

1st

35

11.94 ± 1.98

35

12.20 ± 1.98

0.589

-0.261

ras_willingness

2nd

17

11.12 ± 1.67

0.840

19

12.06 ± 1.71

0.145

0.098

-0.957

ras_goal

1st

35

17.51 ± 3.14

35

17.66 ± 3.14

0.850

-0.079

ras_goal

2nd

17

16.75 ± 2.78

0.419

19

18.23 ± 2.82

-0.314

0.118

-0.812

ras_reliance

1st

35

12.89 ± 2.79

35

13.51 ± 2.79

0.349

-0.497

ras_reliance

2nd

17

13.12 ± 2.30

-0.188

19

14.56 ± 2.36

-0.828

0.067

-1.137

ras_domination

1st

35

10.43 ± 2.16

35

9.60 ± 2.16

0.112

0.544

ras_domination

2nd

17

10.04 ± 2.03

0.257

19

10.33 ± 2.05

-0.477

0.672

-0.190

symptom

1st

35

31.00 ± 9.93

35

29.11 ± 9.93

0.430

0.543

symptom

2nd

17

30.55 ± 7.73

0.130

19

28.43 ± 8.00

0.197

0.421

0.610

slof_work

1st

35

22.51 ± 4.92

35

22.54 ± 4.92

0.981

-0.014

slof_work

2nd

17

22.01 ± 3.95

0.254

19

21.29 ± 4.07

0.627

0.591

0.359

slof_relationship

1st

35

25.37 ± 5.99

35

26.17 ± 5.99

0.578

-0.278

slof_relationship

2nd

17

23.95 ± 5.01

0.493

19

25.72 ± 5.13

0.159

0.301

-0.612

satisfaction

1st

35

19.26 ± 6.97

35

22.37 ± 6.97

0.065

-0.768

satisfaction

2nd

17

19.96 ± 6.17

-0.174

19

21.87 ± 6.26

0.125

0.361

-0.469

mhc_emotional

1st

35

10.89 ± 3.79

35

11.77 ± 3.79

0.331

-0.499

mhc_emotional

2nd

17

11.37 ± 3.15

-0.275

19

11.08 ± 3.22

0.390

0.781

0.167

mhc_social

1st

35

15.37 ± 5.64

35

14.86 ± 5.64

0.704

0.173

mhc_social

2nd

17

16.36 ± 4.85

-0.332

19

14.32 ± 4.94

0.179

0.216

0.684

mhc_psychological

1st

35

21.94 ± 6.35

35

22.83 ± 6.35

0.561

-0.261

mhc_psychological

2nd

17

22.52 ± 5.47

-0.171

19

21.76 ± 5.58

0.314

0.682

0.224

resilisnce

1st

35

16.26 ± 4.34

35

17.00 ± 4.34

0.476

-0.337

resilisnce

2nd

17

16.59 ± 3.69

-0.152

19

17.51 ± 3.77

-0.232

0.462

-0.416

social_provision

1st

35

13.26 ± 2.89

35

14.17 ± 2.89

0.189

-0.576

social_provision

2nd

17

12.86 ± 2.51

0.252

19

14.10 ± 2.56

0.046

0.145

-0.782

els_value_living

1st

35

16.66 ± 2.91

35

18.00 ± 2.91

0.057

-0.887

els_value_living

2nd

17

17.06 ± 2.49

-0.266

19

18.04 ± 2.54

-0.026

0.246

-0.647

els_life_fulfill

1st

35

11.89 ± 3.05

35

13.91 ± 3.05

0.007

-1.224

els_life_fulfill

2nd

17

12.85 ± 2.64

-0.583

19

13.89 ± 2.69

0.016

0.247

-0.624

els

1st

35

28.54 ± 5.33

35

31.91 ± 5.33

0.010

-1.296

els

2nd

17

29.85 ± 4.48

-0.501

19

31.94 ± 4.58

-0.011

0.169

-0.805

social_connect

1st

35

27.74 ± 9.12

35

25.77 ± 9.12

0.369

0.530

social_connect

2nd

17

27.93 ± 7.32

-0.051

19

25.67 ± 7.54

0.027

0.364

0.608

shs_agency

1st

35

13.89 ± 4.91

35

15.29 ± 4.91

0.237

-0.591

shs_agency

2nd

17

14.02 ± 4.11

-0.058

19

15.99 ± 4.21

-0.296

0.160

-0.829

shs_pathway

1st

35

16.23 ± 3.88

35

17.17 ± 3.88

0.313

-0.559

shs_pathway

2nd

17

16.69 ± 3.16

-0.274

19

17.10 ± 3.25

0.040

0.700

-0.245

shs

1st

35

30.11 ± 8.28

35

32.46 ± 8.28

0.240

-0.656

shs

2nd

17

30.68 ± 6.74

-0.159

19

33.12 ± 6.93

-0.185

0.288

-0.683

esteem

1st

35

12.86 ± 1.40

35

12.54 ± 1.40

0.350

0.241

esteem

2nd

17

13.06 ± 1.42

-0.152

19

12.78 ± 1.41

-0.183

0.563

0.210

mlq_search

1st

35

14.80 ± 3.40

35

15.03 ± 3.40

0.779

-0.099

mlq_search

2nd

17

14.69 ± 3.16

0.046

19

14.99 ± 3.19

0.016

0.780

-0.129

mlq_presence

1st

35

13.51 ± 4.04

35

13.69 ± 4.04

0.860

-0.068

mlq_presence

2nd

17

13.54 ± 3.66

-0.012

19

13.74 ± 3.70

-0.020

0.877

-0.076

mlq

1st

35

28.31 ± 6.77

35

28.71 ± 6.77

0.805

-0.093

mlq

2nd

17

28.22 ± 6.16

0.021

19

28.72 ± 6.23

-0.001

0.811

-0.115

empower

1st

35

19.11 ± 3.97

35

20.09 ± 3.97

0.309

-0.503

empower

2nd

17

19.27 ± 3.33

-0.082

19

19.37 ± 3.41

0.368

0.928

-0.053

ismi_resistance

1st

35

14.31 ± 2.54

35

14.89 ± 2.54

0.349

-0.297

ismi_resistance

2nd

17

14.75 ± 2.44

-0.227

19

14.76 ± 2.45

0.068

0.995

-0.003

ismi_discrimation

1st

35

12.26 ± 3.18

35

10.40 ± 3.18

0.017

1.128

ismi_discrimation

2nd

17

11.39 ± 2.71

0.526

19

10.81 ± 2.77

-0.251

0.528

0.352

sss_affective

1st

35

10.57 ± 3.73

35

9.43 ± 3.73

0.204

0.700

sss_affective

2nd

17

10.53 ± 3.04

0.024

19

8.57 ± 3.13

0.526

0.060

1.202

sss_behavior

1st

35

10.49 ± 3.82

35

8.91 ± 3.82

0.090

0.848

sss_behavior

2nd

17

10.42 ± 3.21

0.037

19

8.20 ± 3.28

0.383

0.044

1.194

sss_cognitive

1st

35

8.66 ± 3.94

35

7.89 ± 3.94

0.416

0.466

sss_cognitive

2nd

17

9.55 ± 3.19

-0.539

19

7.11 ± 3.28

0.471

0.026

1.475

sss

1st

35

29.71 ± 10.65

35

26.23 ± 10.65

0.175

0.820

sss

2nd

17

30.57 ± 8.51

-0.202

19

23.93 ± 8.77

0.542

0.023

1.564

Between group

recovery_stage_a

1st

t(96.04) = 0.00, p = 1.000, Cohen d = -0.00, 95% CI (-0.58 to 0.58)

2st

t(101.06) = 0.07, p = 0.944, Cohen d = -0.03, 95% CI (-0.77 to 0.83)

recovery_stage_b

1st

t(90.40) = 0.40, p = 0.691, Cohen d = -0.13, 95% CI (-1.02 to 1.54)

2st

t(100.91) = 0.96, p = 0.341, Cohen d = -0.41, 95% CI (-0.89 to 2.53)

ras_confidence

1st

t(79.89) = 1.22, p = 0.225, Cohen d = -0.53, 95% CI (-0.92 to 3.83)

2st

t(102.00) = 1.14, p = 0.258, Cohen d = -0.60, 95% CI (-1.24 to 4.57)

ras_willingness

1st

t(77.37) = 0.54, p = 0.589, Cohen d = -0.26, 95% CI (-0.69 to 1.20)

2st

t(101.48) = 1.67, p = 0.098, Cohen d = -0.96, 95% CI (-0.18 to 2.06)

ras_goal

1st

t(81.06) = 0.19, p = 0.850, Cohen d = -0.08, 95% CI (-1.35 to 1.64)

2st

t(101.97) = 1.58, p = 0.118, Cohen d = -0.81, 95% CI (-0.38 to 3.32)

ras_reliance

1st

t(75.67) = 0.94, p = 0.349, Cohen d = -0.50, 95% CI (-0.70 to 1.96)

2st

t(100.27) = 1.85, p = 0.067, Cohen d = -1.14, 95% CI (-0.10 to 2.98)

ras_domination

1st

t(88.29) = -1.61, p = 0.112, Cohen d = 0.54, 95% CI (-1.85 to 0.20)

2st

t(101.05) = 0.43, p = 0.672, Cohen d = -0.19, 95% CI (-1.06 to 1.64)

symptom

1st

t(72.42) = -0.79, p = 0.430, Cohen d = 0.54, 95% CI (-6.62 to 2.85)

2st

t(93.82) = -0.81, p = 0.421, Cohen d = 0.61, 95% CI (-7.33 to 3.09)

slof_work

1st

t(74.10) = 0.02, p = 0.981, Cohen d = -0.01, 95% CI (-2.31 to 2.37)

2st

t(98.06) = -0.54, p = 0.591, Cohen d = 0.36, 95% CI (-3.37 to 1.93)

slof_relationship

1st

t(76.71) = 0.56, p = 0.578, Cohen d = -0.28, 95% CI (-2.05 to 3.65)

2st

t(101.12) = 1.04, p = 0.301, Cohen d = -0.61, 95% CI (-1.60 to 5.12)

satisfaction

1st

t(81.29) = 1.87, p = 0.065, Cohen d = -0.77, 95% CI (-0.20 to 6.43)

2st

t(101.95) = 0.92, p = 0.361, Cohen d = -0.47, 95% CI (-2.21 to 6.02)

mhc_emotional

1st

t(76.29) = 0.98, p = 0.331, Cohen d = -0.50, 95% CI (-0.92 to 2.69)

2st

t(100.83) = -0.28, p = 0.781, Cohen d = 0.17, 95% CI (-2.40 to 1.81)

mhc_social

1st

t(78.71) = -0.38, p = 0.704, Cohen d = 0.17, 95% CI (-3.20 to 2.17)

2st

t(101.89) = -1.25, p = 0.216, Cohen d = 0.68, 95% CI (-5.28 to 1.20)

mhc_psychological

1st

t(78.99) = 0.58, p = 0.561, Cohen d = -0.26, 95% CI (-2.13 to 3.91)

2st

t(101.93) = -0.41, p = 0.682, Cohen d = 0.22, 95% CI (-4.41 to 2.90)

resilisnce

1st

t(77.88) = 0.72, p = 0.476, Cohen d = -0.34, 95% CI (-1.32 to 2.81)

2st

t(101.68) = 0.74, p = 0.462, Cohen d = -0.42, 95% CI (-1.55 to 3.39)

social_provision

1st

t(79.72) = 1.32, p = 0.189, Cohen d = -0.58, 95% CI (-0.46 to 2.29)

2st

t(101.99) = 1.47, p = 0.145, Cohen d = -0.78, 95% CI (-0.44 to 2.92)

els_value_living

1st

t(78.39) = 1.93, p = 0.057, Cohen d = -0.89, 95% CI (-0.04 to 2.73)

2st

t(101.82) = 1.17, p = 0.246, Cohen d = -0.65, 95% CI (-0.69 to 2.64)

els_life_fulfill

1st

t(79.47) = 2.78, p = 0.007, Cohen d = -1.22, 95% CI (0.58 to 3.48)

2st

t(101.98) = 1.16, p = 0.247, Cohen d = -0.62, 95% CI (-0.73 to 2.80)

els

1st

t(77.03) = 2.64, p = 0.010, Cohen d = -1.30, 95% CI (0.83 to 5.91)

2st

t(101.31) = 1.39, p = 0.169, Cohen d = -0.80, 95% CI (-0.90 to 5.09)

social_connect

1st

t(74.13) = -0.90, p = 0.369, Cohen d = 0.53, 95% CI (-6.31 to 2.37)

2st

t(98.11) = -0.91, p = 0.364, Cohen d = 0.61, 95% CI (-7.18 to 2.66)

shs_agency

1st

t(76.82) = 1.19, p = 0.237, Cohen d = -0.59, 95% CI (-0.94 to 3.74)

2st

t(101.20) = 1.42, p = 0.160, Cohen d = -0.83, 95% CI (-0.79 to 4.72)

shs_pathway

1st

t(75.01) = 1.02, p = 0.313, Cohen d = -0.56, 95% CI (-0.91 to 2.79)

2st

t(99.50) = 0.39, p = 0.700, Cohen d = -0.24, 95% CI (-1.71 to 2.54)

shs

1st

t(74.89) = 1.18, p = 0.240, Cohen d = -0.66, 95% CI (-1.60 to 6.29)

2st

t(99.34) = 1.07, p = 0.288, Cohen d = -0.68, 95% CI (-2.09 to 6.96)

esteem

1st

t(100.79) = -0.94, p = 0.350, Cohen d = 0.24, 95% CI (-0.98 to 0.35)

2st

t(101.75) = -0.58, p = 0.563, Cohen d = 0.21, 95% CI (-1.21 to 0.66)

mlq_search

1st

t(86.50) = 0.28, p = 0.779, Cohen d = -0.10, 95% CI (-1.39 to 1.85)

2st

t(101.25) = 0.28, p = 0.780, Cohen d = -0.13, 95% CI (-1.80 to 2.40)

mlq_presence

1st

t(83.44) = 0.18, p = 0.860, Cohen d = -0.07, 95% CI (-1.75 to 2.09)

2st

t(101.69) = 0.16, p = 0.877, Cohen d = -0.08, 95% CI (-2.24 to 2.63)

mlq

1st

t(84.28) = 0.25, p = 0.805, Cohen d = -0.09, 95% CI (-2.82 to 3.62)

2st

t(101.56) = 0.24, p = 0.811, Cohen d = -0.12, 95% CI (-3.61 to 4.60)

empower

1st

t(76.96) = 1.02, p = 0.309, Cohen d = -0.50, 95% CI (-0.92 to 2.86)

2st

t(101.27) = 0.09, p = 0.928, Cohen d = -0.05, 95% CI (-2.13 to 2.33)

ismi_resistance

1st

t(91.55) = 0.94, p = 0.349, Cohen d = -0.30, 95% CI (-0.63 to 1.78)

2st

t(100.87) = 0.01, p = 0.995, Cohen d = -0.00, 95% CI (-1.62 to 1.63)

ismi_discrimation

1st

t(78.31) = -2.45, p = 0.017, Cohen d = 1.13, 95% CI (-3.37 to -0.35)

2st

t(101.80) = -0.63, p = 0.528, Cohen d = 0.35, 95% CI (-2.39 to 1.24)

sss_affective

1st

t(75.14) = -1.28, p = 0.204, Cohen d = 0.70, 95% CI (-2.92 to 0.63)

2st

t(99.66) = -1.91, p = 0.060, Cohen d = 1.20, 95% CI (-4.01 to 0.08)

sss_behavior

1st

t(76.89) = -1.72, p = 0.090, Cohen d = 0.85, 95% CI (-3.39 to 0.25)

2st

t(101.23) = -2.04, p = 0.044, Cohen d = 1.19, 95% CI (-4.36 to -0.07)

sss_cognitive

1st

t(74.51) = -0.82, p = 0.416, Cohen d = 0.47, 95% CI (-2.65 to 1.11)

2st

t(98.76) = -2.26, p = 0.026, Cohen d = 1.48, 95% CI (-4.58 to -0.30)

sss

1st

t(73.84) = -1.37, p = 0.175, Cohen d = 0.82, 95% CI (-8.56 to 1.59)

2st

t(97.53) = -2.31, p = 0.023, Cohen d = 1.56, 95% CI (-12.37 to -0.92)

Within treatment group

recovery_stage_a

1st vs 2st

t(49.27) = 1.15, p = 0.512, Cohen d = -0.35, 95% CI (-0.26 to 0.96)

recovery_stage_b

1st vs 2st

t(45.33) = 0.78, p = 0.883, Cohen d = -0.24, 95% CI (-0.75 to 1.70)

ras_confidence

1st vs 2st

t(39.60) = 0.63, p = 1.000, Cohen d = -0.20, 95% CI (-1.21 to 2.30)

ras_willingness

1st vs 2st

t(38.38) = -0.46, p = 1.000, Cohen d = 0.14, 95% CI (-0.77 to 0.49)

ras_goal

1st vs 2st

t(40.19) = 1.00, p = 0.644, Cohen d = -0.31, 95% CI (-0.58 to 1.72)

ras_reliance

1st vs 2st

t(37.56) = 2.60, p = 0.026, Cohen d = -0.83, 95% CI (0.23 to 1.86)

ras_domination

1st vs 2st

t(44.07) = 1.55, p = 0.256, Cohen d = -0.48, 95% CI (-0.22 to 1.67)

symptom

1st vs 2st

t(36.03) = -0.61, p = 1.000, Cohen d = 0.20, 95% CI (-2.94 to 1.58)

slof_work

1st vs 2st

t(36.82) = -1.96, p = 0.114, Cohen d = 0.63, 95% CI (-2.55 to 0.04)

slof_relationship

1st vs 2st

t(38.06) = -0.50, p = 1.000, Cohen d = 0.16, 95% CI (-2.30 to 1.39)

satisfaction

1st vs 2st

t(40.31) = -0.40, p = 1.000, Cohen d = 0.12, 95% CI (-3.07 to 2.06)

mhc_emotional

1st vs 2st

t(37.86) = -1.23, p = 0.454, Cohen d = 0.39, 95% CI (-1.83 to 0.45)

mhc_social

1st vs 2st

t(39.02) = -0.57, p = 1.000, Cohen d = 0.18, 95% CI (-2.43 to 1.37)

mhc_psychological

1st vs 2st

t(39.16) = -1.00, p = 0.651, Cohen d = 0.31, 95% CI (-3.22 to 1.10)

resilisnce

1st vs 2st

t(38.62) = 0.73, p = 0.937, Cohen d = -0.23, 95% CI (-0.90 to 1.92)

social_provision

1st vs 2st

t(39.52) = -0.15, p = 1.000, Cohen d = 0.05, 95% CI (-1.08 to 0.94)

els_value_living

1st vs 2st

t(38.87) = 0.08, p = 1.000, Cohen d = -0.03, 95% CI (-0.93 to 1.01)

els_life_fulfill

1st vs 2st

t(39.40) = -0.05, p = 1.000, Cohen d = 0.02, 95% CI (-1.08 to 1.03)

els

1st vs 2st

t(38.21) = 0.03, p = 1.000, Cohen d = -0.01, 95% CI (-1.64 to 1.70)

social_connect

1st vs 2st

t(36.84) = -0.09, p = 1.000, Cohen d = 0.03, 95% CI (-2.51 to 2.31)

shs_agency

1st vs 2st

t(38.11) = 0.93, p = 0.713, Cohen d = -0.30, 95% CI (-0.82 to 2.22)

shs_pathway

1st vs 2st

t(37.25) = -0.13, p = 1.000, Cohen d = 0.04, 95% CI (-1.16 to 1.02)

shs

1st vs 2st

t(37.19) = 0.58, p = 1.000, Cohen d = -0.19, 95% CI (-1.64 to 2.97)

esteem

1st vs 2st

t(54.46) = 0.62, p = 1.000, Cohen d = -0.18, 95% CI (-0.53 to 1.01)

mlq_search

1st vs 2st

t(43.06) = -0.05, p = 1.000, Cohen d = 0.02, 95% CI (-1.47 to 1.40)

mlq_presence

1st vs 2st

t(41.41) = 0.06, p = 1.000, Cohen d = -0.02, 95% CI (-1.53 to 1.63)

mlq

1st vs 2st

t(41.85) = 0.00, p = 1.000, Cohen d = -0.00, 95% CI (-2.70 to 2.71)

empower

1st vs 2st

t(38.18) = -1.16, p = 0.505, Cohen d = 0.37, 95% CI (-1.95 to 0.53)

ismi_resistance

1st vs 2st

t(46.05) = -0.22, p = 1.000, Cohen d = 0.07, 95% CI (-1.31 to 1.05)

ismi_discrimation

1st vs 2st

t(38.83) = 0.79, p = 0.865, Cohen d = -0.25, 95% CI (-0.64 to 1.46)

sss_affective

1st vs 2st

t(37.31) = -1.65, p = 0.213, Cohen d = 0.53, 95% CI (-1.91 to 0.19)

sss_behavior

1st vs 2st

t(38.14) = -1.21, p = 0.468, Cohen d = 0.38, 95% CI (-1.90 to 0.48)

sss_cognitive

1st vs 2st

t(37.01) = -1.48, p = 0.297, Cohen d = 0.47, 95% CI (-1.85 to 0.29)

sss

1st vs 2st

t(36.70) = -1.70, p = 0.196, Cohen d = 0.54, 95% CI (-5.05 to 0.45)

Within control group

recovery_stage_a

1st vs 2st

t(51.54) = 1.01, p = 0.635, Cohen d = -0.32, 95% CI (-0.32 to 0.96)

recovery_stage_b

1st vs 2st

t(46.97) = -0.15, p = 1.000, Cohen d = 0.05, 95% CI (-1.38 to 1.19)

ras_confidence

1st vs 2st

t(40.37) = 0.37, p = 1.000, Cohen d = -0.12, 95% CI (-1.51 to 2.19)

ras_willingness

1st vs 2st

t(38.97) = -2.52, p = 0.032, Cohen d = 0.84, 95% CI (-1.49 to -0.16)

ras_goal

1st vs 2st

t(41.05) = -1.27, p = 0.424, Cohen d = 0.42, 95% CI (-1.97 to 0.45)

ras_reliance

1st vs 2st

t(38.04) = 0.56, p = 1.000, Cohen d = -0.19, 95% CI (-0.62 to 1.10)

ras_domination

1st vs 2st

t(45.51) = -0.80, p = 0.861, Cohen d = 0.26, 95% CI (-1.38 to 0.60)

symptom

1st vs 2st

t(36.30) = -0.38, p = 1.000, Cohen d = 0.13, 95% CI (-2.84 to 1.93)

slof_work

1st vs 2st

t(37.19) = -0.75, p = 0.912, Cohen d = 0.25, 95% CI (-1.88 to 0.86)

slof_relationship

1st vs 2st

t(38.60) = -1.47, p = 0.297, Cohen d = 0.49, 95% CI (-3.36 to 0.53)

satisfaction

1st vs 2st

t(41.18) = 0.53, p = 1.000, Cohen d = -0.17, 95% CI (-2.00 to 3.41)

mhc_emotional

1st vs 2st

t(38.37) = 0.82, p = 0.832, Cohen d = -0.28, 95% CI (-0.71 to 1.69)

mhc_social

1st vs 2st

t(39.71) = 1.00, p = 0.648, Cohen d = -0.33, 95% CI (-1.01 to 2.99)

mhc_psychological

1st vs 2st

t(39.87) = 0.51, p = 1.000, Cohen d = -0.17, 95% CI (-1.70 to 2.85)

resilisnce

1st vs 2st

t(39.24) = 0.46, p = 1.000, Cohen d = -0.15, 95% CI (-1.15 to 1.82)

social_provision

1st vs 2st

t(40.27) = -0.76, p = 0.904, Cohen d = 0.25, 95% CI (-1.46 to 0.66)

els_value_living

1st vs 2st

t(39.53) = 0.80, p = 0.857, Cohen d = -0.27, 95% CI (-0.62 to 1.42)

els_life_fulfill

1st vs 2st

t(40.13) = 1.76, p = 0.173, Cohen d = -0.58, 95% CI (-0.15 to 2.08)

els

1st vs 2st

t(38.78) = 1.50, p = 0.283, Cohen d = -0.50, 95% CI (-0.45 to 3.06)

social_connect

1st vs 2st

t(37.21) = 0.15, p = 1.000, Cohen d = -0.05, 95% CI (-2.35 to 2.73)

shs_agency

1st vs 2st

t(38.66) = 0.17, p = 1.000, Cohen d = -0.06, 95% CI (-1.47 to 1.74)

shs_pathway

1st vs 2st

t(37.68) = 0.82, p = 0.840, Cohen d = -0.27, 95% CI (-0.69 to 1.61)

shs

1st vs 2st

t(37.62) = 0.47, p = 1.000, Cohen d = -0.16, 95% CI (-1.86 to 3.00)

esteem

1st vs 2st

t(57.52) = 0.50, p = 1.000, Cohen d = -0.15, 95% CI (-0.60 to 1.00)

mlq_search

1st vs 2st

t(44.34) = -0.14, p = 1.000, Cohen d = 0.05, 95% CI (-1.61 to 1.40)

mlq_presence

1st vs 2st

t(42.45) = 0.04, p = 1.000, Cohen d = -0.01, 95% CI (-1.63 to 1.70)

mlq

1st vs 2st

t(42.95) = -0.07, p = 1.000, Cohen d = 0.02, 95% CI (-2.94 to 2.75)

empower

1st vs 2st

t(38.74) = 0.25, p = 1.000, Cohen d = -0.08, 95% CI (-1.15 to 1.46)

ismi_resistance

1st vs 2st

t(47.81) = 0.71, p = 0.964, Cohen d = -0.23, 95% CI (-0.80 to 1.67)

ismi_discrimation

1st vs 2st

t(39.48) = -1.58, p = 0.244, Cohen d = 0.53, 95% CI (-1.97 to 0.24)

sss_affective

1st vs 2st

t(37.75) = -0.07, p = 1.000, Cohen d = 0.02, 95% CI (-1.15 to 1.07)

sss_behavior

1st vs 2st

t(38.70) = -0.11, p = 1.000, Cohen d = 0.04, 95% CI (-1.32 to 1.18)

sss_cognitive

1st vs 2st

t(37.41) = 1.60, p = 0.236, Cohen d = -0.54, 95% CI (-0.24 to 2.02)

sss

1st vs 2st

t(37.05) = 0.60, p = 1.000, Cohen d = -0.20, 95% CI (-2.05 to 3.76)

Plot

Clinical significance